Gender: Male 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Mother's occupation: Homemaker
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to rock/indie music;Go to gigs;Use social media;Exercise;Attend football matches;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Microsoft Bing AI 
LLM use cases: Brainstorming;Generic chatbot conversation;Solving math or logical problems;Generate art;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Entertainment;Creative or artistic;Personal 
Prompt 1: is £1000 enough to start a buisness?
Prompt 2: how do i make money on the stock market quickly ?
Prompt 3: what is the best ai software for making youtube videos?
Prompt 4: what is the best crypto for scalping trading?
Prompt 5: What is the best football team?
Prompt 6: How to use AI to make money?
Prompt 7: What will the world be like in 1 million years?
Prompt 8: is it easy to make money from youtube?
Prompt 9: what type of videos on youtube generate the most views?
Prompt 10: best way to monitor trades